Fix mirostat state when using multiple sequences

common/common.cpp

@@ -940,10 +940,11 @@ llama_token llama_sample_token(
                   struct llama_context * ctx,
                   struct llama_context * ctx_guidance,
                   struct llama_grammar * grammar,
-               const struct gpt_params & params,
+                  struct gpt_params    & params,
         const std::vector<llama_token> & last_tokens,
          std::vector<llama_token_data> & candidates,
-                                   int   idx) {
+        const                      int   idx,
+                          llama_seq_id   seq) {
     const int n_ctx   = llama_n_ctx(ctx);
     const int n_vocab = llama_n_vocab(llama_get_model(ctx));
 
@@ -1011,15 +1012,23 @@ llama_token llama_sample_token(
         // Greedy sampling
         id = llama_sample_token_greedy(ctx, &cur_p);
     } else {
+        float * mirostat_mu = NULL;
+        if (mirostat > 0) {
+            seq = std::max(0, seq); // Deal with people passing -1 or something.
+            auto mu_it = params.sampler_state.find(seq);
+            if (mu_it == params.sampler_state.end()) {
+                const llama_sampler_state new_state = { 2.0f * mirostat_tau };
+                mu_it = params.sampler_state.insert({seq, new_state}).first;
+            }
+            mirostat_mu = &mu_it->second.mirostat_mu;
+        }
         if (mirostat == 1) {
-            static float mirostat_mu = 2.0f * mirostat_tau;
             const int mirostat_m = 100;
             llama_sample_temp(ctx, &cur_p, temp);
-            id = llama_sample_token_mirostat(ctx, &cur_p, mirostat_tau, mirostat_eta, mirostat_m, &mirostat_mu);
+            id = llama_sample_token_mirostat(ctx, &cur_p, mirostat_tau, mirostat_eta, mirostat_m, mirostat_mu);
         } else if (mirostat == 2) {
-            static float mirostat_mu = 2.0f * mirostat_tau;
             llama_sample_temp(ctx, &cur_p, temp);
-            id = llama_sample_token_mirostat_v2(ctx, &cur_p, mirostat_tau, mirostat_eta, &mirostat_mu);
+            id = llama_sample_token_mirostat_v2(ctx, &cur_p, mirostat_tau, mirostat_eta, mirostat_mu);
         } else {
             // Temperature sampling
             size_t min_keep = std::max(1, params.n_probs);

common/common.h

@@ -33,6 +33,10 @@
 //
 int32_t get_num_physical_cores();
 
+typedef struct llama_sampler_state {
+    float mirostat_mu; // mirostat sampler state
+} llama_sampler_state;
+
 struct gpt_params {
     uint32_t seed                           = -1;   // RNG seed
     int32_t n_threads                       = get_num_physical_cores();
@@ -54,6 +58,9 @@ struct gpt_params {
     float   rope_freq_base                  = 0.0f; // RoPE base frequency
     float   rope_freq_scale                 = 0.0f; // RoPE frequency scaling factor
 
+    // per sequence sampler state
+    std::unordered_map<llama_seq_id, llama_sampler_state> sampler_state;
+
     // sampling parameters
     int32_t top_k             = 40;    // <= 0 to use vocab size
     float   top_p             = 0.95f; // 1.0 = disabled
@@ -186,6 +193,9 @@ std::string llama_detokenize_bpe(
 
 // this is a common sampling function used across the examples for convenience
 // it can serve as a starting point for implementing your own sampling function
+// Note: When using multiple sequences, it is the caller's responsibility to delete
+//       the item in params.sampler_state when a sequence ends and samplers that rely on
+//       state are being used.
 //
 // required:
 //  - ctx:    context to use for sampling
@@ -196,6 +206,7 @@ std::string llama_detokenize_bpe(
 //  - grammar:       grammar to use for sampling, ignore if NULL
 //  - last_tokens:   needed for repetition penalty, ignore if empty
 //  - idx:           sample from llama_get_logits_ith(ctx, idx)
+//  - seq:           sequence id to associate sampler state with (currently only used by mirostat)
 //
 // returns:
 //  - token:      sampled token
@@ -205,10 +216,11 @@ llama_token llama_sample_token(
                   struct llama_context * ctx,
                   struct llama_context * ctx_guidance,
                   struct llama_grammar * grammar,
-               const struct gpt_params & params,
+                  struct gpt_params    & params,
         const std::vector<llama_token> & last_tokens,
          std::vector<llama_token_data> & candidates,
-                                   int   idx = 0);
+        const                      int   idx = 0,
+                          llama_seq_id   seq = 0);
 
 //
 // YAML utils

examples/parallel/parallel.cpp

@@ -339,7 +339,7 @@ int main(int argc, char ** argv) {
                 //printf("client %d, seq %d, token %d, pos %d, batch %d\n",
                 //        client.id, client.seq_id, client.sampled, client.n_decoded, client.i_batch);
 
-                const llama_token id = llama_sample_token(ctx, NULL, NULL, params, client.tokens_prev, candidates, client.i_batch - i);
+                const llama_token id = llama_sample_token(ctx, NULL, NULL, params, client.tokens_prev, candidates, client.i_batch - i, client.seq_id);
 
                 if (client.n_decoded == 1) {
                     // start measuring generation time after the first token to make sure all concurrent clients
@@ -384,7 +384,7 @@ int main(int argc, char ** argv) {
 
                     n_total_prompt += client.n_prompt;
                     n_total_gen    += client.n_decoded;
-
+                    params.sampler_state.erase(client.seq_id);
                     client.seq_id = -1;
                 }